Factors Associated with Smoking Cessation and Risk of Smoking Initiation in Bulgarian Youth

The goal of this project was to explore the factors associated with smoking behavior among Bulgarian adolescents. A sample recruited from 12 high schools in Bulgaria (N = 673, mean age = 16.52, 65% female), was used for the analyses in this paper. A series of logistic regressions were performed to explore the factors associated with smoking cessation and increased risk of smoking initiation. Based on self-reported smoking status participants completed different sets of questionnaires and were included in separate models exploring smoking cessation and increased risk of smoking initiation. Variables consistently associated with smoking like stress, coping strategies, peer influence, family influence, exposure to tobacco related marketing were included as predictor variables in both models. In addition each of the two models included the relevant constructs of decisional balance and temptations from the Transtheoretical Model (TTM). The final logistic model differentiating smokers/ex-smokers included age, parental smoking status, Temptation to smoke, and support for smoking bans in public places as variables, correctly classifying 82.3% of the sample. The final model among nonsmokers differentiating higher risk/lower risk of smoking initiation included the strength of the belief that smoking is harmful, Temptations to try smoking, Pros of being smoke-free, and support for smoking bans in public places, correctly classifying 72.7% of the sample. These results provide better understanding of the factors associated with smoking behavior in Bulgarian adolescents that can guide the development of smoking cessation and prevention programs for this population

Psychometric Evaluation of the Care Transition Measures in a Sample of ACS Patients: Results from Transitions, Risks, and Actions in Coronary Events – Center for Outcomes Research and Education (TRACE-CORE)

Background: Quality of transitional care is associated with important health outcomes such as rehospitalization and costs. A widely used measure of the construct, the Care Transitions Measure (CTM-15), was developed with classical test theory approach. Its short version (CTM-3) was included in the CAHPS® Hospital Survey. Methods: As part of TRACE-CORE 1545 participants were interviewed during hospitalization for ACS providing information on general health status (SF-36). At 1 month post-discharge, patients completed CTM-15, health utilization and care process questions. We evaluated the psychometric properties of the CTM using classical and item response theory analyses. We compared the measurement precision of CTM-15, CTM-3, and a CTM-IRT based score using relative validity (RV). Results: Participants were 79% non-Hispanic white, 67% male, 27% with a college education or higher (27%) and average age of 62 years. The CTM scale had good internal consistency (Cronbach’s alpha=0.95), but demonstrated strong acquiescence bias (8.7% participants responded “Strongly agree”, 19% “Agree” to all 15 items) and limited score variability. IRT based item parameters were estimated for all items. The CTM-15 differentiated between groups of patients defined by self-reported health status, health care utilization, and care transition process indicators. Differences between groups were small (2-3 points). There was no gain in measurement precision for the scale from IRT scoring. The CTM-3 was not significantly lower for patients reporting rehospitalization or emergency department visits. Conclusion: We identified psychometric challenges of the CTM, which may limit its value in research and practice. The strong acquiescence bias in the measure leads to highly skewed, clustered scores with restricted score variance. In the absence of guidelines on meaningfully important differences, it is hard to determine whether detected statistically significant differences in CTM are important. These results are in line with emerging evidence of gaps in the validity of the measure

Psychosocial Factors Predict Patient Ratings of Care Transition Quality: Results from Transitions, Risks, and Actions in Coronary Events – Center for Outcomes Research and Education (TRACE-CORE)

Background: Short hospital stays and fragmented care make the transition following hospitalization a high-risk period for ACS patients. Identified risks for rehospitalization and complications associated with transitions include demographic (e.g., older age), clinical (e.g., co-morbidities), and psychosocial (e.g., depression) factors. Thus, one might expect high-risk patients to receive better quality transitional care to minimize negative outcomes; alternatively, the quality of care may be yet another outcome influenced by the same risk factors. Little is known about the predictors of quality of care transitions from the patients’ perspective. Methods: We studied 1,545 TRACE-CORE patients (mean age = 62, 34% female, 78% non-Hispanic white) admitted with an ACS who completed in-hospital interviews and the Care Transition Measure (CTM) at 1 month after discharge. High quality transitions were indicated by a CTM-15 score \u3e74. Using logistic regression models we examined the association between in-hospital demographic, clinical, and psychosocial characteristics, generic and disease specific quality of life, health literacy and numeracy, and cognitive status with high quality transitions. Results: Over one-third (36%) of participants (n=552) reported high quality transitions after an ACS. Most variables of interest were associated (p \u3c .20) with care transition quality in bivariate analyses. After adjustment, in-hospital cognitive impairment (Odds Ratio (OR) 0.68; 95% CI 0.46, 0.98) and older age (OR 0.99; CI 0.98, 1.00) were negatively associated with reporting high care transition quality, while high levels of social support (OR 1.06; CI 1.03, 1.10) and patient activation (OR 1.46; CI 1.02, 2.09) increased the chance of reporting high care transition quality in a multivariable model. Conclusions: Older patients, those with cognitive impairment, low social support, or lower patient activation may be at risk for lower-quality transitions following hospitalization for ACS, and may benefit from extra attention and support during the transition from hospital to home

Incorporating development of a patient-reported outcome instrument in a clinical drug development program: examples from a heart failure program.

BackgroundPatient-reported outcome (PRO) measures can be used to support label claims if they adhere to US Food & Drug Administration guidance. The process of developing a new PRO measure is expensive and time-consuming. We report the results of qualitative studies to develop new PRO measures for use in clinical trials of omecamtiv mecarbil (a selective, small molecule activator of cardiac myosin) for patients with heart failure (HF), as well as the lessons learned from the development process.MethodsConcept elicitation focus groups and individual interviews were conducted with patients with HF to identify concepts for the instrument. Cognitive interviews with HF patients were used to confirm that no essential concepts were missing and to assess patient comprehension of the instrument and items.ResultsDuring concept elicitation, the most frequently reported HF symptoms were shortness of breath, tiredness, fluid retention, fatigue, dizziness/light-headedness, swelling, weight fluctuation, and trouble sleeping. Two measures were developed based on the concepts: the Heart Failure Symptom Diary (HF-SD) and the Heart Failure Impact Scale (HFIS). Findings from cognitive interviews suggested that the items in the HF-SD and HFIS were relevant and well understood by patients. Multiple iterations of concept elicitation and cognitive interviews were needed based on FDA request for a broader patient population in the qualitative study. Lessons learned from the omecamtiv mecarbil PRO/clinical development program are discussed, including challenges of qualitative studies, patient recruitment, expected and actual timelines, cost, and engagement with various stakeholders.ConclusionDevelopment of a new PRO measure to support a label claim requires significant investment and early planning, as demonstrated by the omecamtiv mecarbil program

Psychometric Evaluation of the Care Transition Measure in TRACE‐CORE: Do We Need a Better Measure?

Background: The quality of transitional care is associated with important health outcomes such as rehospitalization and costs. The widely used Care Transitions Measure (CTM‐15) was developed with a classic test theory approach; its short version (CTM‐3) was included in the CAHPS Hospital Survey. We conducted a psychometric evaluation of both measures and explored whether item response theory (IRT) could produce a more precise measure. Methods and Results: As part of the Transitions, Risks, and Actions in Coronary Events Center for Outcomes Research and Education, 1545 participants were interviewed during an acute coronary syndrome hospitalization, providing information on general health status (Short Form‐36), CTM‐15, health utilization, and care process questions at 1 month postdischarge. We used classic and IRT analyses and compared the measurement precision of CTM‐15–, CTM‐3–, and CTM‐IRT–based score using relative validity. Participants were 79% non‐Hispanic white and 67% male, with an average age of 62 years. The CTM‐15 had good internal consistency (Cronbach's α=0.95) but demonstrated acquiescence bias (8.7% participants responded “Strongly agree” and 19% responded “Agree” to all items) and limited score variability. These problems were more pronounced for the CTM‐3. The CTM‐15 differentiated between patient groups defined by self‐reported health status, health care utilization, and care transition process indicators. Differences between groups were small (2 to 3 points). There was no gain in measurement precision from IRT scoring. The CTM‐3 was not significantly lower for patients reporting rehospitalization or emergency department visits. Conclusion: We identified psychometric challenges of the CTM, which may limit its value in research and practice. These results are in line with emerging evidence of gaps in the validity of the measure

Angina Characteristics as Predictors of Trajectories of Quality of Life Following Acute Coronary Syndrome in the Transitions, Risks and Actions in Coronary Events-Center for Outcomes Research and Education cohort (TRACE-CORE)

BACKGROUND: To describe longitudinal trajectories of health-related quality of life (HRQoL) after hospitalization with an acute coronary syndrome (ACS), their associations with baseline angina characteristics, and associations with anxiety, depression, and cognitive impairment. METHODS: TRACE-CORE participants (N=1,613) completed the SF-36 during hospitalization for ACS and 1, 3, & 6 months post-discharge. Latent growth curves identified trajectories of physical and mental components of HRQOL (MCS and PCS) and sequential multiple logistic regression estimated associations between trajectories and angina characteristics. RESULTS: Participants (N=1613) had mean age 63.3 (SD 11.4) years, 33.0% female, and 78.2% non-Hispanic white. We identified 2 MCS trajectories: AVERAGE and IMPAIRED HRQoL. The majority of participants (81.0%) had AVERAGE MCS at baseline (mean MCS 53.6) and slight improvement in scores over time. A minority (19.0%) had IMPAIRED HRQoL at baseline (mean MCS 36.7) and slight improvement in scores over time. We identified 2 similar PCS trajectories with similar patterns of scores over time: AVERAGE (71.1%) and IMPAIRED (28.9%) HRQoL at baseline. Adjusting for demographics & comorbidities, patients with less severe baseline angina were more likely to have AVERAGE MCS (odds ratio [OR]/10 unit change in severity 1.1) and PCS (OR 1.1) trajectories, and similarly for less frequent angina (MCS OR 1.2; PCS OR 1.3). The associations of MCS trajectory with severity and frequency lost significance after adjusting for psychosocial factors, whereas the PCS associations remained significant [All p \u3c 0.05 unless noted]. CONCLUSIONS: About 1/3 of patients exhibited impaired 6-month HRQoL trajectories, which can be predicted by angina characteristics. Psychosocial factors may explain the prediction of mental, not physical, trajectories. Interventions to improve HRQoL after ACS should consider psychosocial factors and angina

Multiple Chronic Conditions and Psychosocial Limitations in a Contemporary Cohort of Patients Hospitalized with an Acute Coronary Syndrome

Background: As adults live longer, multiple chronic conditions have become more prevalent over the past several decades. We describe the prevalence of, and patient characteristics associated with, cardiac and non-cardiac-related multimorbidities in patients discharged from the hospital after an acute coronary syndrome (ACS). Methods: We studied 2,174 patients discharged from the hospital after an ACS at 6 medical centers in Massachusetts and Georgia between April, 2011 and May, 2013. Hospital medical records yielded clinical information including presence of 8 cardiac-related and 8 non-cardiac-related morbidities on admission. We assessed multiple psychosocial characteristics during the index hospitalization using standardized in-person instruments. Results: The mean age of the study sample was 61 years, 67% were men, and 81% were non-Hispanic whites. The most common cardiac-related morbidities were hypertension, hyperlipidemia, and diabetes (76%, 69%, and 31%, respectively). Arthritis, chronic pulmonary disease, and depression (20%, 18%, and 13%, respectively) were the most common non-cardiac morbidities. Patients with ≥4 morbidities (37% of the population) were slightly older and more frequently female than those with 0-1 morbidity; they were also heavier and more likely to be cognitively impaired (26% vs. 12%), have symptoms of moderate/severe depression (31% vs. 15%), high perceived stress (48% vs. 32%), a limited social network (22% vs. 15%), low health literacy (42% vs. 31%), and low health numeracy (54% vs. 42%). Conclusions: Multimorbidity, highly prevalent in patients hospitalized with an ACS, is strongly associated with indices of psychosocial deprivation. This emphasizes the challenge of caring for these patients, which extends well beyond ACS management

Psychometric validation of the generalized pustular psoriasis physician global assessment (GPPGA) and generalized pustular psoriasis area and severity index (GPPASI)

Background: Generalized pustular psoriasis (GPP) is a rare and life-threatening skin disease often accompanied by systemic inflammation. There are currently no standardized or validated GPP-specific measures for assessing severity. Objective: To evaluate the reliability, validity, and responder definitions of the generalized pustular psoriasis physician global assessment (GPPGA) and generalized pustular psoriasis area and severity index (GPPASI). Methods: The GPPGA and GPPASI were validated using outcome data from Week 1 of the Effisayil™ 1 study. The psychometric analyses performed included confirmatory factor analysis, item-to-item/item-to-total correlations, internal consistency reliability, test-retest reliability, convergent validity, known-groups validity, responsiveness analysis, and responder definition analysis. Results: Using data from this patient cohort (N=53), confirmatory factor analysis demonstrated unidimensionality of the GPPGA total score (root mean square error of approximation <0.08), and GPPGA item-to-item and item-to-total correlations ranged from 0.58–0.90. The GPPGA total score, pustulation subscore, and GPPASI total score all demonstrated good test-retest reliability (intraclass correlation coefficient: 0.70, 0.91, and 0.95, respectively), and good evidence of convergent validity. In anchor-based analyses, all three scores were able to detect changes in symptom and disease severity over time; reductions of -1.4, -2.2, and -12.0 were suggested as clinically meaningful improvement thresholds for the GPPGA total score, GPPGA pustulation subscore, and GPPASI total score, respectively. Anchor-based analyses also supported the GPPASI 50 as a clinically meaningful threshold for improvement. Conclusions: Overall, our findings indicate that the GPPGA and GPPASI are valid, reliable, and responsive measures for the assessment of GPP disease severity, and support their use in informing clinical endpoints in trials in GPP

In-hospital Depression Predicts Early Hospital Readmission after an Acute Coronary Syndrome: Preliminary Data from TRACE-CORE

Background: Hospital systems, patients and providers seek to avert rehospitalizations within 30 days for patients admitted with an acute coronary syndrome (ACS). Rehospitalizations within 30 days of discharge are often considered preventable and to reflect poor in-hospital management or discharge practices. However, independent associations of psychosocial factors with early rehospitalization in patients admitted with an ACS have not been examined. Methods: A multi-racial cohort of 1,540 patients admitted with an ACS reported psychosocial factors via standardized questionnaires in an in-hospital interview. One month following discharge, patients were interviewed via phone and reported hospital readmissions. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) of the association between in-hospital psychosocial characteristics (depression, anxiety, and perceived stress), health literacy and numeracy, and cognitive status, with self-reported readmission within 30 days. Results: Participants were 34% female and 17% non-white, with a mean age of 62 years and a mean length of stay of 4.1 days. Rehospitalization was reported for 14% (n=208) of participants, 77% of which were due to CVD. In univariate analyses, in-hospital severe depression, anxiety, and high stress were associated with higher odds of early readmission, whereas low health numeracy was associated with lower odds of early readmission. Severe depression remained associated with higher odds and low health numeracy remained associated with lower odds of early readmission in a multivariable model including covariates associated on univariate testing with rehospitalization. Conclusions: Early readmission after hospitalization for an ACS was common and associated with in-hospital depression and health numeracy. Notably, depression and health numeracy were the only predictors independently associated with readmission in multivariable analyses. We speculate that the lower likelihood of readmission for those with low numeracy may be related to less engagement with the healthcare system. In-hospital screening for depression and characterization of health numeracy may help stratify risk for early rehospitalization after an ACS